Fault detection in solar energy systems: A deep learning approach
ZB Duranay - Electronics, 2023 - mdpi.com
While solar energy holds great significance as a clean and sustainable energy source,
photovoltaic panels serve as the linchpin of this energy conversion process. However …
photovoltaic panels serve as the linchpin of this energy conversion process. However …
Attention deep feature extraction from brain MRIs in explainable mode: Dgxainet
B Taşcı - Diagnostics, 2023 - mdpi.com
Artificial intelligence models do not provide information about exactly how the predictions
are reached. This lack of transparency is a major drawback. Particularly in medical …
are reached. This lack of transparency is a major drawback. Particularly in medical …
Deep learning and artificial intelligence in action (2019-2023): A review on brain stroke detection, diagnosis, and intelligent post-stroke rehabilitation management
J Chaki, M Woźniak - IEEE Access, 2024 - ieeexplore.ieee.org
Brain stroke is a complicated disease that is one of the foremost reasons of long-term
debility and mortality. Because of breakthroughs in Deep Learning (DL) and Artificial …
debility and mortality. Because of breakthroughs in Deep Learning (DL) and Artificial …
Exemplar MobileNetV2-Based Artificial Intelligence for Robust and Accurate Diagnosis of Multiple Sclerosis
T Ekmekyapar, B Taşcı - Diagnostics, 2023 - mdpi.com
Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system that
prominently affects young adults due to its debilitating nature. The pathogenesis of the …
prominently affects young adults due to its debilitating nature. The pathogenesis of the …
Ensemble classification based optimized transfer learning feature method for early stage diagnosis of diabetic retinopathy
Ö Kasim - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
Early diagnosis of the diabetic retinopathy is important in preventing vision loss. The intense
workload of the experts and the long time analysis of the fundus images necessitate a fully …
workload of the experts and the long time analysis of the fundus images necessitate a fully …
Monocyte/hdl cholesterol ratios as a new inflammatory marker in patients with schizophrenia
Purpose: Monocyte/HDL cholesterol ratio (MHR) is a novel inflammatory marker that is used
as a prognostic factor for cardiovascular diseases and has been studied in many diseases …
as a prognostic factor for cardiovascular diseases and has been studied in many diseases …
Enhanced non-contrast computed tomography images for early acute stroke detection using machine learning approach
Early identification of acute stroke lowers the fatality rate since clinicians can quickly decide
on a quick decision of therapy. Brain computed tomography (CT) was one of the imaging …
on a quick decision of therapy. Brain computed tomography (CT) was one of the imaging …
A potential biomarker for predicting schizophrenia: metallothionein-1
It has been thought that oxidative damage may occur in the pathophysiology of
schizophrenia; metallothioneins (MT) have strong antioxidant functions. In this study, we …
schizophrenia; metallothioneins (MT) have strong antioxidant functions. In this study, we …
Motico: An attentional mechanism network model for smart aging disease risk prediction based on image data classification
The current disease risk prediction model with many parameters is complex to run smoothly
on mobile terminals such as tablets and mobile phones in imaginative elderly care …
on mobile terminals such as tablets and mobile phones in imaginative elderly care …
Examination of the Relationship between Peripheral Inflammation Markers and Impulsivity and Aggression in Schizophrenia Patients Involved and Not Involved in …
Aim: The aim of this study was to examine the relationship between peripheral inflammatory
markers and aggression and impulsivity in schizophrenia patients with and without criminal …
markers and aggression and impulsivity in schizophrenia patients with and without criminal …